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      Autism research dynamic through ontology-based text mining

      Advances in Autism
      Emerald Group Publishing Limited
      Text mining, Autism research

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          Abstract

          Purpose – The increase of prevalence of autism spectrum disorders (ASD) has been accompanied by much new research. The amount and the speed of growth of scientific information available online have strongly influenced the way of work in the research community which calls for new methods and tools to support it. The purpose of this paper is to present ontology-based text mining in the field of autism trend analysis that may help to understand the broader picture of the disorder since its discovery. Design/methodology/approach – The data sets consisted of abstracts of more than 18,000 articles on ASD published from 1943 to the end of 2012 found in MEDLINE and of the documents’ titles for all those articles where the abstracts were not available. Findings – In this way, the authors demonstrated a steeper exponential curve of ASD publications compared with all publications in MEDLINE. In addition, the main research topics over time were identified using the “open discovery” approach. Finally, the relationship between a priori setting up research topics including communication, genetics, environmental risk factors, vaccination and adulthood were revealed. Originality/value – Using ontology-based text mining the authors were able to identify the main research topics in the field of autism during the time, as well as to show the dynamics of some research topics as a priori setting up. The computerised methodology that was used allowed the authors to analyse a much larger quantity of information, saving time and manual work.

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          Most cited references6

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          Is Open Access

          A review of research trends in physiological abnormalities in autism spectrum disorders: immune dysregulation, inflammation, oxidative stress, mitochondrial dysfunction and environmental toxicant exposures

          Recent studies have implicated physiological and metabolic abnormalities in autism spectrum disorders (ASD) and other psychiatric disorders, particularly immune dysregulation or inflammation, oxidative stress, mitochondrial dysfunction and environmental toxicant exposures (‘four major areas'). The aim of this study was to determine trends in the literature on these topics with respect to ASD. A comprehensive literature search from 1971 to 2010 was performed in these four major areas in ASD with three objectives. First, publications were divided by several criteria, including whether or not they implicated an association between the physiological abnormality and ASD. A large percentage of publications implicated an association between ASD and immune dysregulation/inflammation (416 out of 437 publications, 95%), oxidative stress (all 115), mitochondrial dysfunction (145 of 153, 95%) and toxicant exposures (170 of 190, 89%). Second, the strength of evidence for publications in each area was computed using a validated scale. The strongest evidence was for immune dysregulation/inflammation and oxidative stress, followed by toxicant exposures and mitochondrial dysfunction. In all areas, at least 45% of the publications were rated as providing strong evidence for an association between the physiological abnormalities and ASD. Third, the time trends in the four major areas were compared with trends in neuroimaging, neuropathology, theory of mind and genetics (‘four comparison areas'). The number of publications per 5-year block in all eight areas was calculated in order to identify significant changes in trends. Prior to 1986, only 12 publications were identified in the four major areas and 51 in the four comparison areas (42 for genetics). For each 5-year period, the total number of publications in the eight combined areas increased progressively. Most publications (552 of 895, 62%) in the four major areas were published in the last 5 years (2006–2010). Evaluation of trends between the four major areas and the four comparison areas demonstrated that the largest relative growth was in immune dysregulation/inflammation, oxidative stress, toxicant exposures, genetics and neuroimaging. Research on mitochondrial dysfunction started growing in the last 5 years. Theory of mind and neuropathology research has declined in recent years. Although most publications implicated an association between the four major areas and ASD, publication bias may have led to an overestimation of this association. Further research into these physiological areas may provide insight into general or subset-specific processes that could contribute to the development of ASD and other psychiatric disorders.
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            A survey of current work in biomedical text mining.

            A. Cohen (2005)
            The volume of published biomedical research, and therefore the underlying biomedical knowledge base, is expanding at an increasing rate. Among the tools that can aid researchers in coping with this information overload are text mining and knowledge extraction. Significant progress has been made in applying text mining to named entity recognition, text classification, terminology extraction, relationship extraction and hypothesis generation. Several research groups are constructing integrated flexible text-mining systems intended for multiple uses. The major challenge of biomedical text mining over the next 5-10 years is to make these systems useful to biomedical researchers. This will require enhanced access to full text, better understanding of the feature space of biomedical literature, better methods for measuring the usefulness of systems to users, and continued cooperation with the biomedical research community to ensure that their needs are addressed.
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              Autism spectrum disorders.

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                Author and article information

                Journal
                10.1108/AIA-01-2016-0001

                Psychology
                Text mining,Autism research
                Psychology
                Text mining, Autism research

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